README.md

---
# Data-files config (Parquet-only)
configs:
- config_name: basic
  data_files:
  - split: test
    path:
      - "basic/test-*.parquet"
      - "basic/test.parquet"
  default: true

- config_name: advanced
  data_files:
  - split: test
    path:
      - "advanced/test-*.parquet"
      - "advanced/test.parquet"

pretty_name: "Gametime"
tags:
  - audio
  - speech
  - tts
  - asr
  - benchmark
task_categories:
  - automatic-speech-recognition
  - text-to-speech
  - audio-to-audio
language:
  - en
license: cc-by-4.0
size_categories:
  - n<100K
---

# Gametime Benchmark

The **Gametime** dataset provides lightweight, streaming-friendly splits for TTS/ASR/SpokenLM prototyping.  
For full details, please refer to the paper:  
👉 [**Game-Time: Evaluating Temporal Dynamics in Spoken Language Models**](https://arxiv.org/abs/2509.26388)

---

## 📦 Download Options

### 1️⃣ Recommended — Full ZIP Download

If you prefer the original folder layout you can download one of the ZIPs packaged in `gametime/download/`. There are two kinds available in this repository:

* `gametime/download/basic_instructions.zip` — unpacks to:

```
basic_instructions/
├── text/
│   ├── *-dataset.json         # per-dataset JSON manifest(s)
├── audios/
│   ├── <dataset_id>/
│   │   └── test/*.wav
├── alignments/                 # per-audio alignment files 
│   ├── <dataset_id>/
│   │   ├── <stem>.jsonl
```

* `gametime/download/advanced_instructions.zip` — unpacks to:

```
advanced_instructions/
├── text/
│   ├── *-dataset.json         # per-dataset JSON manifest(s) with timing tokens
├── audios/
│   ├── <dataset_id>/
│   │   └── test/*.wav
├── alignments/                 # per-audio alignment files 
│   ├── <dataset_id>/
│   │   ├── <stem>.jsonl
```

Notes:

* Each ZIP in `gametime/download/` preserves the original source tree names (`basic_instructions/` or `advanced_instructions/`).

Download example (Hugging Face):

```python
from huggingface_hub import hf_hub_download
import os

path = hf_hub_download(
    repo_id="gametime-benchmark/gametime",
    repo_type="dataset",
    filename="download/basic_instructions.zip",
    revision="main",
    local_dir=".",
)
print("saved to:", path)
```

Unzip example:

```bash
unzip gametime/download/basic_instructions.zip
```

---

### 2️⃣ Optional — Stream from Hugging Face

```python
from datasets import load_dataset

# Load Basic test split
ds_basic = load_dataset("gametime-benchmark/gametime", "basic", split="test", streaming=True)
ex = next(iter(ds_basic))
wav = ex["audio"]["array"]            # numpy float array
sr  = ex["audio"]["sampling_rate"]    # int, e.g. 24000
print(ex["id"], sr, len(wav), ex["text"])

# Load Advanced test split
ds_adv = load_dataset("gametime-benchmark/gametime", "advanced", split="test", streaming=True)
ex_adv = next(iter(ds_adv))
wav_adv = ex_adv["audio"]["array"]
sr_adv  = ex_adv["audio"]["sampling_rate"]
print(ex_adv["id"], sr_adv, len(wav_adv), ex_adv["text"])
```

* Works with **`streaming=True`** — no full download needed
* Audio is auto-decoded via the `datasets` `Audio` feature (requires `soundfile` / libsndfile under the hood)

---

## 📑 Schema

Each row has the following columns (in order):

| # | Column      | Type                       | Description                                                                                                                                                                                                                  |
| - | ----------- | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 1 | `id`        | `string`                   | e.g. `1-a-Sequence-Number/test/1-a-Sequence-Number-11-01.wav`                                                                                                                                                                |
| 2 | `audio`     | `Audio` (24 kHz)           | Auto-decoded audio. Access as `ex["audio"]["array"]` (numpy float array) and `ex["audio"]["sampling_rate"]` (int). The Hugging Face dataset viewer renders this as an inline 🔊 player.                                       |
| 3 | `text`      | `string`                   | Reference transcription / prompt.                                                                                                                                                                                            |
| 4 | `alignment` | `str`                      | alignment metadata                                                                                                                                                                                                            |
| 5 | `dataset`   | `string`                   | Group name (e.g. `1-a-Sequence-Number`).                                                                                                                                                                                     |

Splits: each config (`basic`, `advanced`) provides a single `test` split.

---

## 📚 Citation

If you use this dataset, please cite:

```
@article{chang2025gametime,
  title   = {Game-Time: Evaluating Temporal Dynamics in Spoken Language Models},
  author  = {Kai-Wei Chang and En-Pei Hu and Chun-Yi Kuan and Wenze Ren and Wei-Chih Chen and Guan-Ting Lin and Yu Tsao and Shao-Hua Sun and Hung-yi Lee and James Glass},
  year    = {2025},
  journal = {arXiv preprint arXiv:2509.26388},
  url     = {https://arxiv.org/abs/2509.26388}
}
```

---